基于多元参照光谱的SAM岩性划分方法

doi:10.3724/SP.J.1047.2016.00133

地球信息科学学报 ›› 2016, Vol. 18 ›› Issue (1): 133-140.doi: 10.3724/SP.J.1047.2016.00133

基于多元参照光谱的SAM岩性划分方法

帅爽^1,²(), 张志^2,^*(), 王少军², 陈安^2,³

1. 湖北省国土测绘院,武汉 430010
2. 中国地质大学(武汉)公共管理学院,武汉 430074
3. 武汉市第十四中学,武汉 430061

收稿日期:2015-03-16 修回日期:2015-04-30 出版日期:2016-01-10 发布日期:2016-01-10
通讯作者: 张志 E-mail:100821844@qq.com;zhangz6402@126.com
作者简介:
作者简介：帅爽(1988-),男,硕士,工程师,研究方向为遥感地质。E-mail: 100821844@qq.com
基金资助:
中国地质调查局“航空地球物理和遥感探测技术研发与应用示范”项目(12120113099900)

Lithological Mapping by Multiple Reference Spectra Based SAM

SHUAI Shuang^1,²(), ZHANG Zhi^2,^*(), WANG Shaojun², CHEN An^2,³

1. Hubei Institute of Land Surveying and Mapping, Wuhan 430010, China
2. China University of Geoscience(Wuhan) Public Administration College, Wuhan 430074, China
3. Wuhan Fourteenth High School, Wuhan 430061, China

Received:2015-03-16 Revised:2015-04-30 Online:2016-01-10 Published:2016-01-10
Contact: ZHANG Zhi E-mail:100821844@qq.com;zhangz6402@126.com

摘要/Abstract

摘要：

光谱角制图（SAM）是一种光谱匹配方法,通过量化目标地物光谱与已知参照光谱的相似程度来判断目标地物的类型,广泛应用于多光谱遥感岩性识别。目前,岩石单元训练区内像元的均值光谱,往往作为代表该岩石单元的参照光谱来进行光谱角制图,而使用均值光谱作为参照光谱库的方法,并未考虑岩石单元内部固有的光谱差异性,很大程度上影响了SAM分类效果。为了消除SAM岩性划分时岩石单元内部的光谱差异的影响,本文采用了一种多元参照光谱的SAM岩性划分方法。首先,依据研究区已有地质资料和Landsat-8影像特征,选定各类岩石单元训练区;接着进行各岩石单元训练区内部像元的光谱差异性分析,和各训练区之间的样本可分离性分析,分别使用均值参照光谱库的SAM方法和多元参照光谱库的SAM方法对研究区Landsat-8影像进行了岩性划分实验。研究结果表明,多元参照光谱库的SAM岩性分类方法很好地改善了岩石单元内部光谱差异性对均值参照光谱库的SAM岩性分类方法的影响,分类精度显著提高。

关键词: SAM, 均值参照光谱, 多元参照光谱, 岩性划分, Landsat-8

Abstract:

The spectral angle mapper (SAM) is a spectral matching method. This method can determine the types of target objects through quantifying the spectral similarity between a target pixel spectrum and a known reference spectrum.SAM has been widely used in rock type identi?cation that uses multispectral data. In the most existing studies, a mean re?ectance spectrum of a specific lithological training area has been used as the reference spectrum for the lithological class in SAM. However, the SAM, which uses the mean spectrum, does not take into account the spectral variability, which is an inherent property of many rocks. Andthe spectral variabilityseriously affects SAM classification results.In order to eliminate the impactof the spectral variability inside the lithological classes, a SAM method based on multiple reference spectra is used in this research. First, a geological map of the study area was used to select training areas forfive lithological classes from the Landsat-8 data of the study area.Then the spectral variability inside the lithological classes and the separability between the lithological classeswereexamined. At last, both ofthe SAM with mean reference spectrum and the multiple reference spectra based SAM wereused in lithological mapping of Landsat-8 data in the study area.The results show that the multiple reference spectra based SAM successfully eliminated the influence of the spectral variability on the SAM with mean reference spectrum, and madesigni?cant improvement tothe accuracy of lithological mapping.

Key words: SAM, mean reference spectrum, multiple reference spectra, lithological mapping, Landsat-8

帅爽, 张志, 王少军, 陈安. 基于多元参照光谱的SAM岩性划分方法[J]. 地球信息科学学报, 2016, 18(1): 133-140.DOI:10.3724/SP.J.1047.2016.00133

SHUAI Shuang,ZHANG Zhi,WANG Shaojun,CHEN An. Lithological Mapping by Multiple Reference Spectra Based SAM[J]. Journal of Geo-information Science, 2016, 18(1): 133-140.DOI:10.3724/SP.J.1047.2016.00133

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参考文献 16

[1]	Zhang X Y, Li P J.Lithological mapping from hyperspectral data by improved use of spectral angle mapper[J]. International Journal of Applied Earth Observation and Geoinformation, 2014,31:95-109. doi: 10.1016/j.jag.2014.03.007
[2]	李培军. 用ASETR图像和地统计学纹理进行岩性分类[J].矿物岩石,2004(3):116-120. doi: 10.3969/j.issn.1001-6872.2004.03.014
	[ Li P J.Lithological discrimination using ASTER image and geostatistical texture[J]. Mineral Petrol, 2004,3:116-120. ] doi: 10.3969/j.issn.1001-6872.2004.03.014
[3]	余海阔,李培军.运用LANDSAT ETM+和ASTER数据进行岩性分类[J].岩石学报,2010(1):345-350.
	[ Yu K H, Li P J.Lithologic Mapping Using LANDSAT ETM+ and ASTER Data. Acta Petrologica Sinica, 2010,1:345-350. ]
[4]	宋晚郊,张绪教,高万里,等.东昆仑造山带巴颜喀拉山群ASTER岩性信息提取[J].现代地质,2013,1:116-123. doi: 10.3969/j.issn.1000-8527.2013.01.012
	[ Song W J, Zhang X J, Gao W L, et al.Extraction of lithological information from Bayan Har mountain group of east kunlun orogenic belt using ASTER image. Geoscience, 2013,1:116-123. ] doi: 10.3969/j.issn.1000-8527.2013.01.012
[5]	Lawrence C R.Lithologic mapping in the Mountain Pass, California area using Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data[J]. Remote Sensing of Environment, 2003,84:350-366. doi: 10.1016/S0034-4257(02)00127-X
[6]	Lawrence C R.Lithologic mapping of the Mordor, NT, Australia ultramafic complex by using the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER)[J]. Remote Sensing of Environment, 2005,99:105-126. doi: 10.1016/j.rse.2004.11.021
[7]	Zhang XF.Lithologic and mineral imformation extraction for gold exploration using Aster data in the south chocolate mountains(California)[J]. Journal of Photogrammetry &Remote Sensing, 2007,62:271-282.
[8]	Kruse F A, Lefkoff A B, Boardman J W, et al.The spectral image processing system (SIPS)-interactivevisualization and analysis of imaging spectrometer data[J]. Remote Sensing of Environment, 1993,44:145-163. doi: 10.1016/0034-4257(93)90013-N
[9]	Crosta A P, Sabine C, Taranik J V.Hydrothermal alteration mapping at Bodie,California, using AVIRIS hyperspectraldata[J]. Remote Sensing of Environment, 1998,65:309-319. doi: 10.1016/S0034-4257(98)00040-6
[10]	Murphy RJ, Monteiro ST, Schneider S.Evaluating classification techniques for mapping vertical geology using field-based hyperspectral sensors[J]. IEEE Transactions on GeoscienceAndRemote Sensing, 2012,50:3066-3080. doi: 10.1109/TGRS.2011.2178419
[11]	Hecker C, van der Meijde M, van der Werff H, et al. Assessingthe influence of reference spectra on synthetic SAM classification results[J]. IEEETransactions on Geoscience and Remote Sensing, 2008,46:4162-4172. doi: 10.1109/TGRS.2008.2001035
[12]	Bowers T L, Rowan L C.Remote mineralogic and lithologic mapping of theice river alkaline complex, British Columbia, Canada, using AVIRIS data[J]. Photogrammetric Engineering &. Remote Sensing, 1996,62:1379-1386. doi: 10.1029/96PA01490
[13]	Chen X F, Warner T A, Campagna D J.Integrating visible, near-infrared andshort-wave infrared hyperspectral and multispectral thermal imagery for geo-logical mapping at Cuprite, Nevada[J]. Remote Sensing Environment, 2007,110:344-356. doi: 10.1016/j.rse.2007.03.015
[14]	Harris J, McGregor R, Budkewitsch P. Geological analysis of hyperspectraldata over southwest Baffin Island: methods for producing spectral maps thatrelate to variations in surface lithologies[J]. Canadian Journal of Remote Sensing, 2010,36:412-435.
[15]	Zhang J, Rivard B, Sanchez-Azofeifa A.Intra- and inter-classspectral variability of tropical tree species at La Selva, Costa Rica: Implicationsfor species identification using HYDICE imagery[J]. Remote Sensing Environment, 2006,105:129-141.
[16]	Cho M A, Debba P, Mathieu R, et al.Improving discrimination of savanna tree species through a multiple-endmember spectral angle mapper approach: canopy-level analysis[J]. IEEE Transactions on Geoscience and Remote Sensing, 2010,48:4133-4142. doi: 10.1109/TGRS.2010.2058579

	K₁	K₂	K₃	E₁	E₂
均值	2.5742	3.2127	2.7956	3.4711	2.7143
标准差	1.4546	1.6973	1.2803	1.8437	1.4631

J-M距离	K₁	K₂	K₃	E₁	E₂
K₁		1.989	1.998	1.993	2.000
K₂	1.989		1.869	1.960	1.995
K₃	1.998	1.869		1.989	1.981
E₁	1.993	1.960	1.989		2.000
E₂	2.000	1.995	1.981	2.000

训练区	K₁	K₂	K₃	E₁	E₂
原始像元数	64	30	64	36	63
剩余像元数	60	28	55	27	55
像元剔除率（％）	6.25	6.67	14.06	25.00	12.70

类别	均值参照光谱库的SAM			多元参照光谱库的SAM
类别	生产者精度（％）		用户精度（％）	生产者精度（％）	用户精度（％）
K₁	68.21	95.98		93.39	96.93
K₂	58.80	92.98		80.03	63.44
K₃	89.07	64.48		89.43	80.44
E₁	45.21	34.78		72.10	93.66
E₂	91.40	90.96		85.11	98.06
总体精度	76.8057		86.4557
Kappa系数	0.6989		0.8250

基于多元参照光谱的SAM岩性划分方法

Lithological Mapping by Multiple Reference Spectra Based SAM

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